An approach to support generic topologies in distributed PSO algorithms in Spark

Pardo, Xoán C.; González, Patricia; Banga, Julio R.; Doallo, Ramón

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http://hdl.handle.net/2183/36703

An approach to support generic topologies in distributed PSO algorithms in Spark

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Pardo_XoanC_2023_An_approach_to_support_generic_topologies_in_distributed_PSO_algorithms_in_Spark.pdf (220.76 KB)

Identifiers

URI: http://hdl.handle.net/2183/36703

DOI: 10.35537/10915/155281

Publication date

2023

Authors

Pardo, Xoán C.

González, Patricia

Banga, Julio R.

Doallo, Ramón

Bibliographic citation

Pardo, X. C., González, P., Banga, J. R., & Doallo, R. (2023). An approach to support generic topologies in distributed PSO algorithms in Spark. In XI Jornadas de Cloud Computing, Big Data & Emerging Topics (La Plata, 27 al 29 de junio de 2023).

Abstract

[Abstract] Particle Swarm Optimization (PSO) is a popular population-based search algorithm that has been applied to all kinds of complex optimization problems. Although the performance of the algorithm strongly depends on the social topology that determines the interaction between the particles during the search, current Metaheuristic Optimization Frameworks (MOFs) provide limited support for topologies. In this paper, we present an approach to support generic topologies in distributed PSO algorithms within a framework for the development and execution of population- based metaheuristics in Spark, which is currently under development.